Design and Preliminary Findings of Adherence to the Self-Testing for Our Protection From COVID-19 (STOP COVID-19) Risk-Based Testing Protocol: Prospective Digital Study
dc.contributor.author | Herbert, Carly | |
dc.contributor.author | Broach, John | |
dc.contributor.author | Gerber, Ben S | |
dc.contributor.author | Fahey, Nisha | |
dc.contributor.author | Orvek, Elizabeth Aaker | |
dc.contributor.author | Lazar, Peter | |
dc.contributor.author | Ferranto, Julia M. | |
dc.contributor.author | Noorishirazi, Kamran | |
dc.contributor.author | Valpady, Shivakumar | |
dc.contributor.author | Shi, Qiming | |
dc.contributor.author | Lin, Honghuang | |
dc.contributor.author | Marvel, Kathryn | |
dc.contributor.author | Gibson, Laura L | |
dc.contributor.author | Barton, Bruce A | |
dc.contributor.author | Lemon, Stephenie C | |
dc.contributor.author | Hafer, Nathaniel | |
dc.contributor.author | McManus, David D | |
dc.contributor.author | Soni, Apurv | |
dc.date | 2022-08-11T08:10:20.000 | |
dc.date.accessioned | 2022-08-23T17:04:37Z | |
dc.date.available | 2022-08-23T17:04:37Z | |
dc.date.issued | 2022-06-16 | |
dc.date.submitted | 2022-07-19 | |
dc.identifier.citation | <p>Herbert C, Kheterpal V, Suvarna T, Broach J, Marquez JL, Gerber B, Schrader S, Nowak C, Harman E, Heetderks W, Fahey N, Orvek E, Lazar P, Ferranto J, Noorishirazi K, Valpady S, Shi Q, Lin H, Marvel K, Gibson L, Barton B, Lemon S, Hafer N, McManus D, Soni A. Design and Preliminary Findings of Adherence to the Self-Testing for Our Protection From COVID-19 (STOP COVID-19) Risk-Based Testing Protocol: Prospective Digital Study. JMIR Form Res. 2022 Jun 16;6(6):e38113. doi: 10.2196/38113. PMID: 35649180; PMCID: PMC9205422. <a href="https://doi.org/10.2196/38113">Link to article on publisher's site</a></p> | |
dc.identifier.issn | 2561-326X (Linking) | |
dc.identifier.doi | 10.2196/38113 | |
dc.identifier.pmid | 35649180 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14038/44673 | |
dc.description | <p>Full author list omitted for brevity. For the full list of authors, see article.</p> | |
dc.description.abstract | BACKGROUND: Serial testing for SARS-CoV-2 is recommended to reduce spread of the virus; however, little is known about adherence to recommended testing schedules and reporting practices to health departments. OBJECTIVE: The Self-Testing for Our Protection from COVID-19 (STOP COVID-19) study aims to examine adherence to a risk-based COVID-19 testing strategy using rapid antigen tests and reporting of test results to health departments. METHODS: STOP COVID-19 is a 12-week digital study, facilitated using a smartphone app for testing assistance and reporting. We are recruiting 20,000 participants throughout the United States. Participants are stratified into high- and low-risk groups based on history of COVID-19 infection and vaccination status. High-risk participants are instructed to perform twice-weekly testing for COVID-19 using rapid antigen tests, while low-risk participants test only in the case of symptoms or exposure to COVID-19. All participants complete COVID-19 surveillance surveys, and rapid antigen results are recorded within the smartphone app. Primary outcomes include participant adherence to a risk-based serial testing protocol and percentage of rapid tests reported to health departments. RESULTS: As of February 2022, 3496 participants have enrolled, including 1083 high-risk participants. Out of 13,730 tests completed, participants have reported 13,480 (98.18%, 95% CI 97.9%-98.4%) results to state public health departments with full personal identifying information or anonymously. Among 622 high-risk participants who finished the study period, 35.9% showed high adherence to the study testing protocol. Participants with high adherence reported a higher percentage of test results to the state health department with full identifying information than those in the moderate- or low-adherence groups (high: 71.7%, 95% CI 70.3%-73.1%; moderate: 68.3%, 95% CI 66.0%-70.5%; low: 63.1%, 59.5%-66.6%). CONCLUSIONS: Preliminary results from the STOP COVID-19 study provide important insights into rapid antigen test reporting and usage, and can thus inform the use of rapid testing interventions for COVID-19 surveillance. | |
dc.language.iso | en_US | |
dc.relation | <p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=35649180&dopt=Abstract">Link to Article in PubMed</a></p> | |
dc.rights | Copyright © Carly Herbert, Vik Kheterpal, Thejas Suvarna, John Broach, Juan Luis Marquez, Ben Gerber, Summer Schrader, Christopher Nowak, Emma Harman, William Heetderks, Nisha Fahey, Elizabeth Orvek, Peter Lazar, Julia Ferranto, Kamran Noorishirazi, Shivakumar Valpady, Qiming Shi, Honghuang Lin, Kathryn Marvel, Laura Gibson, Bruce Barton, Stephenie Lemon, Nathaniel Hafer, David McManus, Apurv Soni. Originally published in JMIR Formative Research (https://formative.jmir.org), 16.06.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | COVID-19 | |
dc.subject | COVID-19 testing | |
dc.subject | SARS-CoV-2 | |
dc.subject | adherence | |
dc.subject | coronavirus | |
dc.subject | digital health | |
dc.subject | digital surveillance | |
dc.subject | disease spread | |
dc.subject | health application | |
dc.subject | health care | |
dc.subject | infectious disease | |
dc.subject | mHealth | |
dc.subject | mobile health | |
dc.subject | prevention | |
dc.subject | public health | |
dc.subject | rapid antigen tests | |
dc.subject | reporting | |
dc.subject | smartphone app | |
dc.subject | surveillance | |
dc.subject | vaccination | |
dc.subject | UMCCTS funding | |
dc.subject | Behavioral Medicine | |
dc.subject | Community Health and Preventive Medicine | |
dc.subject | Health Information Technology | |
dc.subject | Health Services Administration | |
dc.subject | Health Services Research | |
dc.subject | Infectious Disease | |
dc.subject | Preventive Medicine | |
dc.subject | Virus Diseases | |
dc.title | Design and Preliminary Findings of Adherence to the Self-Testing for Our Protection From COVID-19 (STOP COVID-19) Risk-Based Testing Protocol: Prospective Digital Study | |
dc.type | Journal Article | |
dc.source.journaltitle | JMIR formative research | |
dc.source.volume | 6 | |
dc.source.issue | 6 | |
dc.identifier.legacyfulltext | https://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1186&context=prc_pubs&unstamped=1 | |
dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/prc_pubs/186 | |
dc.identifier.contextkey | 30311122 | |
refterms.dateFOA | 2022-08-23T17:04:37Z | |
html.description.abstract | <p>BACKGROUND: Serial testing for SARS-CoV-2 is recommended to reduce spread of the virus; however, little is known about adherence to recommended testing schedules and reporting practices to health departments.</p> <p>OBJECTIVE: The Self-Testing for Our Protection from COVID-19 (STOP COVID-19) study aims to examine adherence to a risk-based COVID-19 testing strategy using rapid antigen tests and reporting of test results to health departments.</p> <p>METHODS: STOP COVID-19 is a 12-week digital study, facilitated using a smartphone app for testing assistance and reporting. We are recruiting 20,000 participants throughout the United States. Participants are stratified into high- and low-risk groups based on history of COVID-19 infection and vaccination status. High-risk participants are instructed to perform twice-weekly testing for COVID-19 using rapid antigen tests, while low-risk participants test only in the case of symptoms or exposure to COVID-19. All participants complete COVID-19 surveillance surveys, and rapid antigen results are recorded within the smartphone app. Primary outcomes include participant adherence to a risk-based serial testing protocol and percentage of rapid tests reported to health departments.</p> <p>RESULTS: As of February 2022, 3496 participants have enrolled, including 1083 high-risk participants. Out of 13,730 tests completed, participants have reported 13,480 (98.18%, 95% CI 97.9%-98.4%) results to state public health departments with full personal identifying information or anonymously. Among 622 high-risk participants who finished the study period, 35.9% showed high adherence to the study testing protocol. Participants with high adherence reported a higher percentage of test results to the state health department with full identifying information than those in the moderate- or low-adherence groups (high: 71.7%, 95% CI 70.3%-73.1%; moderate: 68.3%, 95% CI 66.0%-70.5%; low: 63.1%, 59.5%-66.6%).</p> <p>CONCLUSIONS: Preliminary results from the STOP COVID-19 study provide important insights into rapid antigen test reporting and usage, and can thus inform the use of rapid testing interventions for COVID-19 surveillance.</p> | |
dc.identifier.submissionpath | prc_pubs/186 | |
dc.contributor.department | Prevention Research Center | |
dc.contributor.department | Morningside Graduate School of Biomedical Sciences | |
dc.contributor.department | Division of Cardiovascular Medicine, Department of Medicine | |
dc.contributor.department | Division of Infectious Diseases and Immunology, Department of Medicine | |
dc.contributor.department | Division of Clinical Informatics, Department of Medicine | |
dc.contributor.department | UMass Center for Clinical and Translational Science | |
dc.contributor.department | Department of Pediatrics | |
dc.contributor.department | Department of Population and Quantitative Health Sciences | |
dc.contributor.department | Department of Emergency Medicine | |
dc.contributor.department | Program in Digital Medicine, Department of Medicine | |
dc.source.pages | e38113 |
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COVID-19 Publications by UMass Chan Authors [665]
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